Something old, something new, something borrowed, something blue

# Something old, something new, something borrowed, something blue
## Ways to teach data science (and learn it too!)
### Dr. Chester Ismay Data Science Curriculum Lead at DataCamp GitHub: <a href="https://github.com/ismayc">ismayc</a> Twitter: <a href="https://twitter.com/old_man_chester">@</a><a href="https://twitter.com/old_man_chester">old_man_chester</a>
### 2017-10-19 (ASA Oregon Chapter Fall 2017 meeting) Slides available at <a href="http://bit.ly/asa-ismay17" class="uri">http://bit.ly/asa-ismay17</a> Free Reproducible Textbook at <a href="http://ModernDive.com" class="uri">http://ModernDive.com</a>

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Something Old

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## `#`chalktalk

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## Take notes by hand (sometimes even code by hand)

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## At the very least, lecture slows down a bit

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Something New

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## Learning to program is like learning a foreign language

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## DataCamp - Learning by Doing

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## DataCamp + Collaborative Classroom + `#`chalktalk

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## What can students do in this paradigm?

### From no programming background to half a semester in this style

- [Write vignettes for the `fivethirtyeight` R package](http://soc301s2017.netlify.com/group-projects/)
- [Analyze data interesting to them in a reproducible way](https://rudeboybert.github.io/MATH116/PS/final_project/final_project_outline.html#past_examples)

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## Empower your students/yourself to do great things with data science and they/you will!

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Something Borrowed

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## Open source, crowd-sourced

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## Textbooks should have versions instead of editions

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["If you are not embarrassed by the first version of your product, you’ve launched too late."](http://www.businessinsider.com/the-iterate-fast-and-release-often-philosophy-of-entrepreneurship-2009-11)

>> Reid Hoffman, founder of LinkedIn

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# No more errata

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Something BLUE?

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## Driven by data visualization

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## Focus on randomization methods

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## New developments

### [The `infer` package](https://infer.netlify.com)

```r
install.packages("devtools")
devtools::install_github("ismayc/infer", ref = "dev")
library(infer)
```

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## Future plans

- Implement all of the intro stats inference examples in the `infer` package
  - Generalize functions so it is useful to practioners as well as students
- Rewrite the inference part of the ModernDive book
- Extend the modeling part of the book ([work in progress](https://ismayc.github.io/moderndiver-book/6-regression.html))
- Embed more interactivity using our [free DataCamp course](https://www.datacamp.com/courses/effective-data-storytelling-using-the-tidyverse) into the book for more student practice
- Lead more workshops on using the `infer` package to extend knowledge of the `tidyverse`, R, and statistics

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# Thanks for attending!

- Special thanks to [Albert Y. Kim](https://twitter.com/rudeboybert) and [Andrew Bray](https://andrewpbray.github.io)
- Slides created via the R package [xaringan](https://github.com/yihui/xaringan) by Yihui Xie
- Slides available at <http://bit.ly/asa-ismay17>
- Source code for these slides at <https://github.com/ismayc/talks/asa-oregon-fall17>